QVeris Tech Earnings Deepdive
Use this skill for technology-company earnings deep dives adapted from Tech Earnings Deepdive. Preserve the multi-perspective memo shape, but convert subjective or investment-action language into evidence, scenarios, uncertainty, and verification steps backed by QVeris CAP tools.
Source record:
| Field | Value |
|---|---|
| Candidate number | 6 |
| Original repository | Tech Earnings Deepdive |
| GitHub URL | https://github.com/webleon/tech-earnings-deepdive-openclaw-skill |
| License | MIT |
| Evaluation recent activity | 2026-03-24 |
| Local source snapshot | third_party/source_repos/06-tech-earnings-deepdive |
| Snapshot latest commit | 5bff060 on 2026-03-24 |
Runtime Contract
- Use only
qveris_finance.*CAP tools andQVERIS_API_KEY. - Resolve entities with
ref_symbology,ref_security_master, andref_company_profile. - Accept
dry_run,max_calls,max_age, andbudget_note; if omitted in a natural-language request, default todry_run=false,max_calls=12,max_age=P1D, and a conservative budget note, then echo those controls. - Every thesis, counter-thesis, segment trend, management quote, and reaction datapoint must include
qveris_trace. - Show
missing_fieldsand confidence; do not infer missing competitive or segment data as fact. - Treat QVeris
_meta.source_provideras provenance only; never call, request credentials for, or depend on those internal providers directly. - Suppress
analyst_target_price,target_price, price-objective, upside, buy/sell, and recommendation fields even if a QVeris payload contains them. - Sanity-check entity, market, date window, fiscal period, and payload shape before using data; if a payload is stale, cross-period, truncated, or semantically mismatched, mark it in
data_qualityandmissing_fields.
Workflows
- Tech earnings deep dive:
earnings_actual_surprise,fundamentals_segment,estimates_consensus,transcripts_earnings_call,news_fin_tagged. - Competition/moat:
ref_classification_theme,research_analyst_reports,alt_patents,alt_job_postings,alt_supply_chain. - Valuation/reaction:
mkt_l1_rt,mkt_bars_intraday,mkt_after_hours,fundamentals_derived_ratios.
Live Fallback Policy
- If
fundamentals_segmentis not discovered or returns a provider error, fall back tonews_fin_tagged,transcripts_earnings_call, andestimates_consensusfor segment commentary context. - Do not produce a segment scorecard as if segment revenue/margin data were present; move segment gaps to
missing_fields. - If
transcripts_earnings_callorearnings_actual_surprisefails, do not present a full earnings deep dive; label the output as an estimates/news/market fallback memo. - Use
alt_patents,research_analyst_reports, and theme outputs only after checking they are actually patents, sell-side/research-like reports, or technology themes for the requested company. - Set
qveris_trace[].fallback_used: trueand includeprimary_tool_unavailablefor any conclusion based on fallback context.
Output Requirements
- Use
schemas/output.schema.json. - Include thesis, evidence, contrary evidence, segment scorecard, risk, missing data, and next verification steps.
- Do not output a position decision, buy/sell point, or target price commitment.
- Include
data_qualitywith status, stale fields, out-of-window events, and suppressed fields when applicable. - End with:
不构成投资建议 / Not investment advice.
Prohibited Capabilities
Do not use original non-QVeris earnings/news/valuation/competition sources, EODHD, Yahoo, FMP, Alpha Vantage, Polygon, AkShare, Snowball, Sina, SEC scraping, Longbridge, FinViz, Alpaca, browser automation, cookies, login state, third-party API keys, automated trading, wallet/swap, buy/sell points, position decisions, portfolio action instructions, or target price commitments.
References
- Read
references/qveris-tool-map.mdbefore choosing tool calls. - Use
fixtures/qveris/sample-output.jsonas the minimum output shape.